用于通信保障航天器遗传蚁群融合路径规划

孙兆伟1; 刘雪奎1; 吴限德2; 邓泓1

doi:10.3788/OPE.20132112.3308

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用于通信保障航天器遗传蚁群融合路径规划

信息科学 | 更新时间：2020-08-12

- 用于通信保障航天器遗传蚁群融合路径规划
- Path planning based on ant colony and genetic fusion algorithm for communication supporting spacecraft
- 光学精密工程 2013年21卷第12期页码：3308-3316
- 作者机构：
  
  1. 哈尔滨工业大学卫星技术研究所，黑龙江哈尔滨 150080
  2. 哈尔滨工程大学航天与建筑工程学院，黑龙江哈尔滨 150001
- 作者简介：
- 基金信息：
  
  中央高校基本科研业务费(3122015C016)
- DOI：10.3788/OPE.20132112.3308
  中图分类号： TP391;V412.4+1
- 收稿日期：2013-08-29，
  
  修回日期：2013-09-13，
  
  网络出版日期：2013-12-25，
  
  纸质出版日期：2013-12-25
- 稿件说明：
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孙兆伟, 刘雪奎, 吴限德, 邓泓. 用于通信保障航天器遗传蚁群融合路径规划[J]. 光学精密工程, 2013,21(12): 3308-3316

SUN Zhao-Wei, LIU Xue-Kui, TUN Xian-De, DENG Hong. Path planning based on ant colony and genetic fusion algorithm for communication supporting spacecraft[J]. Editorial Office of Optics and Precision Engineering, 2013,21(12): 3308-3316
孙兆伟, 刘雪奎, 吴限德, 邓泓. 用于通信保障航天器遗传蚁群融合路径规划[J]. 光学精密工程, 2013,21(12): 3308-3316 DOI： 10.3788/OPE.20132112.3308.

SUN Zhao-Wei, LIU Xue-Kui, TUN Xian-De, DENG Hong. Path planning based on ant colony and genetic fusion algorithm for communication supporting spacecraft[J]. Editorial Office of Optics and Precision Engineering, 2013,21(12): 3308-3316 DOI： 10.3788/OPE.20132112.3308.

摘要

为实现通信保障航天器的大范围轨道机动，提出了融合遗传和蚁群算法的通信保障航天器机动路径规划方法。首先，建立了空间飞行器的轨道运动模型，在此基础上研究了遗传算法和蚁群算法的融合策略，利用遗传算法在初期的快速收敛性以及蚁群算法在后期的高效性，分别设计了融合算法中的遗传算法和蚁群算法，并给出融合算法的运行过程。最后，对本文提出的路径规划进行了仿真验证。结果表明：融合算法完成100次迭代后，目标函数即可达到稳定区间；安全路径平均长度为4.055 3104 m。结果验证了基于遗传-蚁群融合算法的机动轨道规划具有更快的收敛速度，能够在更短的时间内规划出到达故障航天器的飞行路径，显著提高了规划效率。

Abstract

To implement the orbit maneuvering of a communication supporting spacecraft in a large area

the path planning of the communication supporting spacecraft was proposed based on the fusion of ant colony and genetic algorithms. Firstly

the orbit dynamic model of spacecraft was established

and the fusion scheme of the genetic and ant colony algorithms was studied. On the basis of the fast convergence of genetic algorithm and the higher efficiency of colony algorithm

the genetic and ant colony algorithms were redesigned respectively under a fusion framework

and the operation process was presented. Finally

the path planning was simulated. The simulation results show that the fusion algorithm can reach the stabilization after 100 iterations

and the average safety path length is 4.055 3104 m. These results prove that the convergence speed of maneuvering orbit planning based on genetic and ant colony fusion is fast

and the flight path to a fault of spacecraft can be obtained in a shorter time

which raises the efficiency of orbit planning remarkably. Key words: path planning; genetic algorithm; ant colony algorithm; orbital maneuvering; communication supporting spacecraft

关键词

Keywords

references

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